Value in Chains: Analytics without Tears or Fears

In the previous issue, I discussed some different optimization planes in Digital Analytics which can certainly be applied, at least in part, to Marketing Analytics in general. My point was to bring to the reader’s attention that there are more than one way, more than one dimension to squeeze a maximum of insight juice from, and that optimization was not all about conversion funnel improvement.

In the same vein, not all analyses are created equal, and there are certainly some that are more valuable than others. How do you define an analysis value then, you will ask (gosh I love having brilliant readers!)? Well, we can obviously debate for a long time about value, but let me say that the closer to increasing profitability an analysis is (which is by the way very close to a company’s future valuation, and everybody loves working with one’s own future in mind), the more valuable it is. This does not mean that all analysis types should be profit analyses, but that you should be able to link it to a chain of analytics activities that ultimately focuses on profitability.

This is also what I mean by Digital Analytics Value Chain.

In and Out

At a very fundamental level, as Nicolas Malo and I showed in our book, analytics work is a matter of maximizing output (transactions, leads, views, etc.) from the same input (visits to online property visits, phone calls, etc.).

Simple, yes, but often forgotten. I mean, if you want to double your online sales, double your traffic! There, you know how to do it now. If doubling one’s traffic was that easy and cheap, though… The whole purpose of Analytics is thus to extract maximum value from the same input; if not, why care? You don’t need Analytics.

Of course, this simple model (I’m almost ashamed of calling it a model) gets way more complicated in practicality:

All those arrows (and there are others) can be the focus of your analysis and optimization activities. Again, as I mentioned in last’s month issue, we are here at a very mechanical plane. By that I mean that all you have to do is to tight a screw here, a bolt there, and you get value. No need for complex models, sophisticated stochastic predictions; simple comparison, A/B testing, usage of control groups, etc., will point you to the direction of value.

Pebbles and Breadcrumbs

So, in the same spirit, we can take a specific process and determine how valuable Analytics can be at the various steps of that process, hence the “value chain” metaphor. Let me illustrate that with an image from a recent webinar, here giving an example from a lead generation process:

From the square “Traffic”, the more you go to the right, the more valuable the analysis. Well, sort of, but you get my point. Profitability of each activity, and customer file analyses, could certainly be performed as well, as segmentation for each point, here by source of traffic, as illustrated, or even by customer segments. It is valuable to analyze traffic, but traffic to critical content has even more value, and analysis of specific critical visitor actions even more, and so forth. Analyzing what kind of customers you acquire (and beware of increasing conversion of bad ones!), how loyal they stay, how profitable they are (and unequal from that profitability standpoint), will give you a picture of your company’s future. No surprise that asking how many visitors we got last week should be seen as the least valuable question one can ask.

My whole point here is to tell you to take the time to map out your value creation process, and map your analytics accordingly. You most probably already perform several types of analysis. Explicitly mapping your analytics value chain will help you a lot with figuring where and how to get the most value back from your marketing investments (and your investments in Analytics as well, for that matter), while making it easier to communicate your Analytics strategy.